Lying Your Way to Better Traffic Engineering

TL;DR

This paper introduces COYOTE, a traffic engineering scheme that uses strategic misinformation to optimize IP network traffic flow, outperforming existing methods in robustness and efficiency under uncertain traffic conditions.

Contribution

The paper presents COYOTE, a novel traffic engineering approach that employs controlled misinformation to improve network performance and robustness against traffic variability.

Findings

COYOTE significantly outperforms current TE schemes.

It is robust to traffic demand uncertainties.

Prototype implementation demonstrates practical deployability.

Abstract

To optimize the flow of traffic in IP networks, operators do traffic engineering (TE), i.e., tune routing-protocol parameters in response to traffic demands. TE in IP networks typically involves configuring static link weights and splitting traffic between the resulting shortest-paths via the Equal-Cost-MultiPath (ECMP) mechanism. Unfortunately, ECMP is a notoriously cumbersome and indirect means for optimizing traffic flow, often leading to poor network performance. Also, obtaining accurate knowledge of traffic demands as the input to TE is elusive, and traffic conditions can be highly variable, further complicating TE. We leverage recently proposed schemes for increasing ECMP's expressiveness via carefully disseminated bogus information ("lies") to design COYOTE, a readily deployable TE scheme for robust and efficient network utilization. COYOTE leverages new algorithmic ideas to configure (static) traffic splitting ratios that are optimized with respect to all (even adversarially chosen) traffic scenarios within the operator's "uncertainty bounds". Our experimental analyses show that COYOTE significantly outperforms today's prevalent TE schemes in a manner that is robust to traffic uncertainty and variation. We discuss experiments with a prototype implementation of COYOTE.